README.md

In PLORN: Prediction with Less Overfitting and Robust to Noise

PLORN

The goal of PLORN is to provide the functions to construct a prediction model of environments using noisy omics data linked with the environments based on PLORN algorithm.

Installation

You can install the development version of PLORN from GitHub with: #install.packages(“devtools”) devtools::install_github(“takakoizumi/PLORN”)

Example

install.packages(“PLORN”) library(PLORN) # basic example code data(Pinus) x.train <- Pinus[[1]] x.test <- Pinus[[2]] y <- Pinus[[3]] cor(y, plorn(x.train, y, newx = x.test, n.pred = 100))

PLORN documentation built on March 21, 2022, 9:11 a.m.